학술논문

A Federated Machine Learning Protocol for Fog Networks
Document Type
Conference
Source
IEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) Computer Communications Workshops (INFOCOM WKSHPS), IEEE INFOCOM 2021 - IEEE Conference on. :1-6 May, 2021
Subject
Communication, Networking and Broadcast Technologies
Performance evaluation
Protocols
Conferences
Force
Machine learning
Computer architecture
Internet of Things
Federated learning
edge computing
fog networking
Language
Abstract
In this paper, we present a federated learning (FL) protocol for fog networking applications. The fog networking architecture is compatible with the Internet of Things (IoT) edge computing concept of the Internet Engineering Task Force (IETF). The FL protocol is designed and specified for constrained IoT devices extended to the cloud through the edge. The proposed distributed edge intelligence solution is tested through experimental trials for specific application scenarios. The results depicts the performance of the proposed FL protocol in terms of accuracy of the intelligence and latency of the messaging. Next generation Internet will rely on such protocols, which can deploy edge intelligence more efficient to the extreme amount of newly connected IoT devices.